De-interlacing processing method and device, and computer-readable storage medium

ABSTRACT

A de-interlacing processing method, a de-interlacing processing device and a computer-readable storage medium are provided. The method includes acquiring image content characteristic information of a pixel point to be interpolated; and determining according to the image content characteristic information whether a de-interlacing algorithm based on motion adaptive or a de-interlacing algorithm based on motion compensation is adopted to perform de-interlacing processing.

CROSS-REFERENCE TO RELATED APPLICATION

The present application claims the priority to the Chinese PatentApplication No. 201811504273.4 filed with the CNIPA on Dec. 10, 2018,the entire contents of which are incorporated here by reference.

TECHNICAL FIELD

The present disclosure relates to a de-interlacing processing method, ade-interlacing processing device and a computer-readable storage medium.

BACKGROUND

Interlaced scanning is to divide each frame of image into an odd fieldand an even field, and a line scan frequency, a frequency spectrum ofvideo signals, and a channel bandwidth for transmission of the videosignals of the interlaced scanning are half of those in progressivescanning. Due to early undeveloped communication technology, theinterlaced scanning is widely used in analog televisions in the existingart for saving the limited bandwidth. However, the interlaced scanninghas some disadvantages, such as flickering, image jitter and jaggedvertical edges.

Moreover, the de-interlacing processing methods in the existing art alsohave their own disadvantages.

SUMMARY

At least one embodiment of the present disclosure provides ade-interlacing processing method, a de-interlacing processing device anda computer-readable storage medium.

At least one embodiment of the present disclosure provides ade-interlacing processing method, including: acquiring image contentcharacteristic information of a pixel point to be interpolated; anddetermining according to the image content characteristic informationwhether a de-interlacing algorithm based on motion adaptive (MA) or ade-interlacing algorithm based on motion compensation (MC) is adopted toperform de-interlacing processing.

At least one embodiment of the present disclosure provides ade-interlacing processing device, including a memory storing a program,and a processor. When the program is read and executed by the processor,the method according to any one embodiment is implemented.

At least one embodiment of the present disclosure provides acomputer-readable storage medium storing one or more programs which areexecutable by one or more processors to perform the method according toany one embodiment.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flowchart illustrating a de-interlacing processing methodaccording to an embodiment of the present disclosure;

FIG. 2 is a schematic diagram of fields;

FIG. 3 is a schematic diagram of an M×N pixel block according to anembodiment of the present disclosure;

FIGS. 4a and 4b are schematic diagrams illustrating de-interlacingprocessing according to an embodiment of the present disclosure;

FIG. 5 is a block diagram illustrating de-interlacing based on MA;

FIG. 6 is a schematic diagram illustrating a processing mode ofde-interlacing processing based on MA;

FIG. 7 is a block diagram illustrating de-interlacing based on MC;

FIG. 8 is a schematic diagram illustrating de-interlacing processingbased on MC;

FIG. 9 is a schematic diagram illustrating a processing mode ofde-interlacing processing based on MC;

FIG. 10 is a schematic diagram of edge directions;

FIG. 11 is a schematic diagram of a 5×5 pixel block used in calculationof a drawing-feathering flag;

FIG. 12 is a schematic diagram of a de-interlacing processing deviceaccording to an embodiment of the present disclosure; and

FIG. 13 is a schematic diagram of a computer-readable storage mediumaccording to an embodiment of the present disclosure.

DETAILED DESCRIPTION

The embodiments of the present disclosure will be described below withreference to the accompanying drawings. The embodiments and the featuresof the embodiments in the present disclosure can be arbitrarily combinedwith each other without conflict.

The steps illustrated in the flowcharts of the accompanying drawings maybe performed in a computer system such as a set of computer-executableinstructions. Moreover, although a logical order is illustrated in theflowchart, the steps illustrated or described may be performed in anorder different from that described herein in some cases.

In an embodiment, de-interlacing (DIT) is a process of converting aninterlaced video image into a progressive video image. Mainde-interlacing algorithms include a de-interlacing algorithm based on MAand a de-interlacing algorithm based on MC.

The de-interlacing processing method provided by the present disclosurecan combine the de-interlacing algorithm based on MA and thede-interlacing algorithm based on MC. The de-interlacing processingmethod according to the embodiments can realize adaptive selection ofthe above two algorithms according to image content characteristics.

As shown in FIG. 1, an embodiment of the present disclosure provides ade-interlacing processing method, including steps 1010 and 1020.

At the step 1010, image content characteristic information of a pixelpoint to be interpolated is acquired.

At the step 1020, whether a de-interlacing algorithm based on MA or ade-interlacing algorithm based on MC is adopted to performde-interlacing processing is determined according to the image contentcharacteristic information.

Compared with the existing art, the interlacing processing methodaccording to the embodiment includes acquiring the image contentcharacteristic information of the pixel point to be interpolated, anddetermining according to the image content characteristic informationwhether the de-interlacing algorithm based on MA or the de-interlacingalgorithm based on MC is adopted to perform de-interlacing processing.The solution provided by the embodiment can achieve selecting differentde-interlacing processing solutions according to the image contentcharacteristic information. The de-interlacing algorithm based on MA hasthe advantages of simple implementation, and good processing effects onstatic images or non-horizontal edge texture of any moving object in animage. The de-interlacing algorithm based on MC has the advantages thatno information is lost under a condition that a motion vector (MV)obtained by Motion Estimation (ME) is accurate, so that detailinformation of an object can be kept, resulting in better quality of ade-interlaced image.

In an embodiment, the image content characteristic information includesat least one of MV information, inter-field matching information,inter-frame matching information, edge direction information of thepixel point to be interpolated, and drawing-feathering intensityinformation.

The MV information may be obtained based on any standard algorithm, suchas a matching algorithm based on sum of absolute differences (SAD) ofblocks.

The edge direction information refers to the information obtained indetection of an edge direction of the pixel point to be interpolated.The detection of the edge direction is separately performed in a currentfield Fn and a last field Fn−1, and may be implemented with any generaledge direction detection method, such as a method using the Sobeloperator.

In FIG. 2, Fn−2 to Fn+1 are four fields (images of fields), Fn is acurrent field, Fn−1 and Fn+1 are a last (or previous) field and a nextfield relative to the current field, and Fn−2 is a last field relativeto Fn−1. anl, an, anr, bnl, bn and bnr are pixel points in the field Fn,cn_1l, cn_1 and cn_1r are pixel points in the field Fn−1, an_2l, an_2,an_2r, bn_2l, bn_2 and bn_2r are pixel points in the field Fn−2, andcn1l, cn1 and cn1r are pixel points in the field Fn+1. The fields Fn andFn+1 constitute a current frame curr_frame, and the fields Fn−2 and Fn−1constitute a last frame last_frame likewise. an and bn are pixel pointsin the field Fn, and luminance component values of an and bn are Yan andYbn, respectively. In the following description, Yx represents aluminance component value of a pixel point x which may be an, bn, cn1,cn_1, etc, and Y[i][j] represents luminance of a pixel point in Row iand Column j. The de-interlacing algorithm is a process ofreconstructing a new progressive image by interpolating a new row ofpixels between an upper row and a lower row of the current field and. InFIG. 2, the pixel point filled with oblique lines in the field Fn is acurrent pixel to be reconstructed, and is also called a pixel to beinterpolated (i.e., a pixel point to be interpolated). The presentdisclosure is described below by taking the luminance component as anexample, and a de-interlacing processing method in case of a chrominancecomponent is completely the same as the method described herein.

The inter-field matching information is determined with the followingmethod: selecting a first pixel block composed of M pixels in a last (orprevious) row relative to a current row where the pixel point to beinterpolated is located and a second pixel block composed of M pixels ina next row relative to the current row from a current field, determiningmatched blocks of the first pixel block and the second pixel block in alast field relative to the current field, obtaining a first sum ofabsolute differences (first SAD) according to the first pixel block andthe matched block thereof, and a second SAD according to the secondpixel block and the matched block thereof, and taking a maximum value ofthe first SAD and the second SAD as the inter-field matchinginformation. A central position of the M pixels in the last row and acentral position of the M pixels in the next row are in the same columnas the pixel point to be interpolated, that is, the M pixels in the lastrow relative to the pixel point to be interpolated and the M pixels inthe next row relative to the pixel point to be interpolated are foundwith the pixel point to be interpolated taken as a center, and M is apositive integer.

In other embodiments, the first SAD or the second SAD may be directlytaken as the inter-field matching information.

In addition, in other embodiments, the inter-field matching informationmay be determined by selecting a first pixel block composed of M pixelsin a last row relative to the pixel point to be interpolated and asecond pixel block composed of M pixels in a next row relative to thepixel point to be interpolated from a current field, determining matchedblocks of the first pixel block and the second pixel block in a nextfield, obtaining a third SAD and a fourth SAD, and taking a maximumvalue of the third SAD and the fourth SAD as the inter-field matchinginformation. The central position of the M pixels in the last row andthe central position of the M pixels in the next row are in the samecolumn as the pixel point to be interpolated, that is, the M pixels inthe last row relative to the pixel point to be interpolated and the Mpixels in the next row relative to the pixel point to be interpolatedare found with the pixel point to be interpolated taken as a center. Inother embodiments, the third SAD or the fourth SAD may be directly takenas the inter-field matching information sad_field.

In an embodiment, the inter-frame matching information is determinedwith the following method: forming a current frame from a current fieldwhere the pixel point to be interpolated is located and a next fieldrelative to the current field, selecting a pixel block in a preset sizewith the pixel point to be interpolated taken as a center, and matchingthe pixel block with a pixel block in a last frame relative to thecurrent frame to obtain the inter-frame matching information. In anembodiment, the inter-frame matching information may be obtained bymatching the pixel block with a pixel block in a next frame relative tothe current frame. For example, the images of the current field Fn andthe next field Fn+1 constitute a current frame image frm_curr, and theimages of the fields Fn−2 and Fn−1 constitute a last frame imagefrm_last. Similar to the calculation of the inter-field matchinginformation, matching is performed after an MV is calculated. A block ina preset size (such as 6=6) is selected with the current pixel point tobe interpolated taken as a center, and matching is performed on the 6×6block to calculate an inter-frame matching value sad_frame.

In an embodiment, the drawing-feathering intensity information isdetermined with at least one of the following methods:

an M×N pixel block with the pixel point to be interpolated as a centeris taken from a synthesized frame composed of a current field and a lastfield; for the M×N pixel block, an accumulated value of differencesbetween pixel values corresponding to adjacent pixel points ofheterogeneous field in a column and an accumulated value of differencesbetween pixel values corresponding to adjacent pixel points ofhomogeneous field in the column are calculated column by column; and thenumber of the columns satisfyingsame_parity_value[i]*coeff<dif_parity_value[i] is obtained, wheresame_parity_value[i] is an accumulated value of differences betweenpixel values corresponding to adjacent pixel points of homogeneous fieldin Column i in the M×N pixel block, dif_parity_value[i] is anaccumulated value of differences between pixel values corresponding toadjacent pixel points of heterogeneous field in Column i in the M×Npixel block, i=0˜N−1, and coeff is greater than 0; and, when the numberof the columns satisfying same_parity_value[i]*coeff<dif_parity_value[i]is greater than a first threshold, the drawing-feathering intensityinformation is greater than a drawing intensity threshold;

for the M×N pixel block, an accumulated value of pixels in each row isacquired to obtain M accumulated values sum_value_ver[l], where l=0˜M−1;(M−2) thresholdsthr[j]=|(sum_value_ver[j+1]*2−sum_value_ver[j]−sum_value_ver[j+2]| areobtained according to the M accumulated values, where j=0˜M−3, M isgreater than or equal to 3, and N is greater than or equal to 1;

for the M×N pixel block, differences between pixel values correspondingto adjacent pixel points of homogeneous field and differences betweenpixel values corresponding to adjacent pixel points of heterogeneousfield are calculated point by point;

frame_diff[j][i]=|Y[j][i]−Y[j+2][i]|

field_diff[j][i]=|Y[j][i]−Y[j+1][i]|

where i=0˜N−1;

when the number of columns satisfying

$\begin{matrix}{{{{thr}\lbrack j\rbrack} > {{{{frame\_ diff}\lbrack j\rbrack}\lbrack i\rbrack}^{*}{factor}\; 1}}{{{thr}\lbrack j\rbrack} < {{{{field\_ diff}\lbrack j\rbrack}\lbrack i\rbrack}^{*}{factor}\; 2}}} & \;\end{matrix}$

is greater than a second threshold, the drawing-feathering intensityinformation is greater than the drawing intensity threshold, wherefactor1 and factor2 are regulatory factors for drawing detection and aregreater than 0, Y[j][i] is a value of a pixel point in Row j and Columni in the M×N pixel block, such as a luminance value or a chrominancevalue, frame_diff[j][i] is a difference between pixel valuescorresponding to adjacent pixel points of homogeneous field for thepixel point in Row j and Column i in the M×N pixel block, andfield_diff[j][i] is a difference between pixel values corresponding toadjacent pixel points of heterogeneous field for the pixel point in Rowj and Column i in the M×N pixel block. In an embodiment, factor1 andfactor2 range from 0 to 20. In an embodiment, a flag may be used toindicate whether the drawing intensity information is greater than thedrawing intensity threshold; and bob_flag=1 is set to indicate that thedrawing intensity information is greater than the drawing intensitythreshold.

As shown in FIG. 3, in the M×N pixel block, the accumulated value of thedifferences between the pixel values of the adjacent pixel points ofheterogeneous field in a column is calculated column by column:

the accumulated value of the differences between the pixel values of thepixel points of heterogeneous field in Column i isdif_parity_value[i]=Σ_(j=0) ^(M-2)|Y[j][i]−Y[j+1][i]|, where Y[j][i] isa value of the pixel point in Row j and Column i in the M×N pixel block,such as a luminance value or a chrominance value.

The accumulated value of the differences between the pixel values of thepixel points of homogeneous field in Column i in the M×N pixel block issame_parity_value[i]=Σ_(j=0) ^(M-3)|Y[j][i]−Y[j+2][i]|; and

for the M×N pixel block, the accumulated value of the pixels in each rowis acquired, for example, the accumulated value of Row 1 issum_value_ver[l]=Σ_(i=0) ^(N-1)|Y[l][i]|, and the accumulated value ofRow 0 is sum_value_ver[0]=Σ_(i=0) ^(N-1)|Y[0][i]|.

The pixels of homogeneous field refer to the pixels in the same field,and the pixels of heterogeneous field refer to the pixels in differentfields.

The MV information is used to evaluate motions in an image, and theinter-field matching information and the inter-frame matchinginformation are used to evaluate the similarity between a current filedand an adjacent field or an adjacent frame. In an embodiment, theinter-frame matching information and the inter-field matchinginformation may be other information that can be used to evaluate thesimilarity.

When an MV is 0 or indicates that current motion intensity meets amotion intensity threshold condition, the de-interlacing algorithm basedon MA is adopted to perform de-interlacing processing. Thede-interlacing processing based on MC is very sensitive to the MVobtained by the ME, and thus has a high requirement for accuracy of theMV obtained by the ME. The MV may be not reliable enough when an objectrotates or is deformed, which may cause compensation errors. That is,the de-interlacing algorithm based on MA is adopted to performde-interlacing processing in the case where the motion intensity is high(or meets the motion intensity threshold condition), thereby avoidingthe compensation errors caused by the algorithm based on MC.

The inter-field matching information and the inter-frame matchinginformation indicate the similarity between fields or frames. In thecase of small similarity (a similarity threshold may be set, and thesimilarity is regarded as small similarity when the similarity is lessthan the similarity threshold), the de-interlacing algorithm based on MAis adopted to perform de-interlacing processing.

The edge direction information is used to determine whether an edgedirection is a horizontal direction (the horizontal direction is a rowdirection in the image (i.e., a scanning direction)). If the edgedirection is a non-horizontal direction, the de-interlacing algorithmbased on MA is adopted to perform de-interlacing processing. As thede-interlacing processing based on MA uses intra-field directionalinterpolation for motions, the information of some horizontal edgetextures may be lost, resulting in image flickering and blurring. In theembodiment, the de-interlacing processing based on MA is adopted in thecase of non-horizontal direction, thereby avoiding the image flickeringand blurring caused by the loss of the information.

The drawing-feathering intensity information is used to evaluate adifference between adjacent rows in a synthesized frame. When the motionchanges significantly between two fields, the drawing-featheringintensity information is large. Therefore, when the drawing-featheringintensity information is greater than a drawing intensity threshold, thede-interlacing algorithm based on MA is adopted to performde-interlacing processing, which can avoid the problem of compensationerrors caused by the high requirement of the algorithm based on MC forthe accuracy of MV in the case of large motion intensity, therebyimproving an image effect.

When none of the above conditions is met, the de-interlacing algorithmbased on MC is adopted to perform de-interlacing processing.

In an embodiment, the step of determining according to the image contentcharacteristic information whether the de-interlacing algorithm based onMA or the de-interlacing algorithm based on MC is adopted to performde-interlacing processing includes:

when one of the following conditions is satisfied, adopting thede-interlacing algorithm based on MA to perform de-interlacingprocessing; and

when none of the following conditions is satisfied, adopting thede-interlacing algorithm based on MC to perform de-interlacingprocessing; and

the conditions include at least one of:

a MV of the pixel point to be interpolated is 0;

an absolute value of any component of the MV of the pixel point to beinterpolated is greater than a preset number of integer pixels, with theMV having two components;

the inter-field matching information is greater than a first inter-fieldmatching threshold, and the inter-frame matching information is greaterthan a first inter-frame matching threshold;

the inter-field matching information is greater than a secondinter-field matching threshold, and the inter-frame matching informationis greater than a second inter-frame matching threshold;

the inter-field matching information is greater than the inter-framematching information, and the inter-frame matching information isgreater than a third inter-frame matching threshold;

the first edge direction information of the pixel point to beinterpolated in the current field indicates a non-horizontal direction;

the second edge direction information of the pixel point to beinterpolated in the last field indicates a non-horizontal direction;

the third edge direction information of the pixel point to beinterpolated in the next field indicates a non-horizontal direction; and

the drawing intensity information is greater than the drawing intensitythreshold. That is, when the drawing-feathering intensity is too large,the de-interlacing processing based on MA is performed.

In an embodiment, the first inter-field matching threshold ranges from 0to 300;

the second inter-field matching threshold ranges from 200 to 600;

the first inter-frame matching threshold ranges from 200 to 700;

the second inter-frame matching threshold ranges from 100 to 500; and

the third inter-frame matching threshold ranges from 0 to 300.

In an embodiment, the above ranges are merely examples, and other valuesmay be taken as required.

In an embodiment, the step of performing de-interlacing processing usingthe de-interlacing algorithm based on MC includes:

acquiring a first value of the pixel point to be interpolated calculatedby the de-interlacing algorithm based on MA;

acquiring a second value of the pixel point to be interpolatedcalculated by a de-interlacing algorithm based on forward motioncompensation;

acquiring a third value of the pixel point to be interpolated calculatedby a de-interlacing algorithm based on backward motion compensation; and

performing median filtering on the first value, the second value and thethird value, and taking a result of the median filtering as a value ofthe pixel point to be interpolated calculated by the de-interlacingalgorithm based on MC.

In other embodiments, performing de-interlacing processing by using thede-interlacing algorithm based on MC may acquire the second value or thethird value, or select one of the second value and the third value

The present disclosure is illustrated by an embodiment. As shown inFIGS. 4a and 4b , a de-interlacing method according to an embodiment ofthe present disclosure includes steps 401 to 404.

At step 401, de-interlacing processing based on MA is performed on avideo. Motion detection is performed on a current pixel, aninterpolation result of an intra-field direction is selected as a resultof the MA de-interlacing if the pixel is in motion, and a pixel at acorresponding position in the other field of a current frame is copiedas an output of the MA de-interlacing if the pixel is static.

As shown in FIG. 5, a process of the de-interlacing algorithm based onMA includes performing motion detection on a current pixel point,outputting move_flag, and, if the current pixel point is static,selecting a pixel point corresponding to one of Ycn_1, Ycn1 and(Ycn_1+Ycn1)/2, which is closest to both Yan and Ybn, as a finalreconstructed pixel output for a current pixel point to be interpolated.Specifically, Ycn_1, Ycn1 and (Ycn_1+Ycn 1)/2 are compared with(Yan+Ybn)/2, and one of Ycn_1, Ycn1 and (Ycn_1+Ycn 1)/2, the differencebetween which and (Yan+Ybn)/2 is the smallest, is selected as the finaloutput. Yan, Ybn and Ycn1 herein are the luminance components of thecurrent frame, and the chrominance components are processed in the sameway as the luminance components. an and bn are the upper pixel point andthe lower pixel point relative to the current pixel point to beinterpolated, and cn_1 and cn1 are the pixel points at the correspondingpositions in the last field and the next field, respectively.

If the current pixel point is in motion, the intra-field interpolationresult is used as the final reconstructed pixel output. The intra-fieldinterpolation usually adopts an intra-field interpolation algorithmbased on an edge direction.

As shown in FIG. 6, if an angle of an edge direction at the pixel pointto be interpolated is θ6, and two pixel points, which are closest to thepixel point to be interpolated along the edge direction, are b0 and a6,the current intra-field interpolation of the pixel point to beinterpolated is (Yb0+Ya6)/2. The intra-field interpolation is performedin a similar way in the case where the angle of the edge direction isanother angle. The final result of MA de-interlacing is denoted by a.

In an embodiment, a de-interlacing method based on MA is not limited tothe above method, and may be a modification or suitable extension of theabove method.

At step 402, de-interlacing processing based on MC is performed on thevideo. An image is divided into N×N blocks, and each block is subjectedto ME to obtain an MV of the block. Bidirectional motion compensation(i.e., forward motion compensation and backward motion compensation) isperformed according to the obtained MVs. The results of the forwardmotion compensation, the backward motion compensation and thede-interlacing based on MA are input to a 3-input median filter toobtain a result of de-interlacing based on MC.

As shown in FIG. 7, the image is divided into blocks. An MV at the pixelpoint to be interpolated in a block is calculated block by block. Themethod of calculating the MV may be any standard algorithm, such as amatching algorithm based on SADs of the blocks. The higher the accuracyof MV, the better, depending on the complexity of hardwareimplementation and the cost of the implementation. In the algorithm ofthe present disclosure, corresponding motion compensation values of theMV in an image of the last field and an image of the next field need tobe obtained, that is, obtaining a forward motion compensation value anda backward motion compensation value respectively.

The process of motion compensation is described below by taking forwardmotion compensation as an example. As show in FIG. 8, a pixel block 41in a current field Fn is a current block, a matched block of the pixelblock 41 in a field Fn−1 is a block 42, and an MV at this time is asshown in FIG. 8. During motion compensation, the block 42 and thecurrent block 41 are interlaced and combined (as shown in FIG. 9) intoone frame block in the field Fn according to the value of MV, therebycompleting the de-interlacing of the block 41 based on forward motioncompensation. All the blocks in the field are subjected tode-interlacing in the same way as the block 41 to complete thede-interlacing of the entire field and obtain a value b. In anembodiment, there are two interlacing ways according to thecharacteristics of the current field, as shown in FIG. 9.

Similarly, as shown in FIG. 8, a matched block 43 in a field Fn+1 iscorresponding to the current block 41, and the current block 41 and thecorresponding matched block 43 in Fn+1 can be interlaced and combinedinto a frame block to complete the de-interlacing based on backwardmotion compensation, that is, obtaining a backward compensation value c.

The above steps 401 and 402 can be performed in parallel.

In an embodiment, the output of the de-interlacing based on MC isobtained by inputting the results of the forward motion compensation,the backward motion compensation, and the de-interlacing based on MA toa 3-input median filter and performing median filtering. The finalresult based on MC is: mc=median (a, b, c). The median filtering refersto taking a median, that is, outputting a median of the sequence of a, band c.

In other embodiments, the median filtering may not be performed. Theoutput of the de-interlacing algorithm based on MC may be the resultobtained by the forward motion compensation, or the result obtained bythe backward motion compensation, or either one of the result obtainedby the forward motion compensation and the result obtained by thebackward motion compensation, or one of the result obtained by theforward motion compensation and the result obtained by the backwardmotion compensation selected according to a certain principle.

At step 403, image content characteristics of the pixel point to beinterpolated are calculated, with the image content characteristicsincluding inter-frame matching information, inter-field matchinginformation, edge direction information, a drawing-feathering flag and aMV value.

In an embodiment, the calculation and determination of the image contentcharacteristics are carried out pixel by pixel rather than block byblock.

The acquisition of the image content characteristics includes:

(a) The acquisition of the inter-field matching information:

M pixels in a last row relative to the pixel point to be interpolatedand M pixels in a next row relative to the pixel point to beinterpolated are selected from the current field Fn, and arerespectively matched with an MV value (MV_(x), Mv_(y)) of the field Fn−1obtained by calculation to obtain two SADs, that is, sad_u and sad_d.The maximum value of the two SADs is selected as a final matching valuesad_field, that is, sad_field=MAX(sad_u, sad_d).

The calculation method of the SADs is as follows:

${SAD} = {\sum\limits_{i = 0}^{M - 1}{{{{YF}_{n}( {{x + i},y} )} - {Y{F_{n - 1}( {{x + i + {mv_{x}}},{y + {mv_{y}}}} )}}}}}$

where YF_(n)(x+i,y) is the luminance of a pixel point with coordinates(x+i,y) in the field Fn, and YF_(n-1)(x+i+mv_(x),y+mv_(y)) is theluminance of a pixel point with coordinated (x+i+mv_(x),y+mv_(y)) in thefield Fn−1. The value of M may be set as required.

(b) The acquisition of the inter-frame matching information:

The images of the current field Fn and the next field Fn+1 constitute acurrent frame image frm_curr, and the images of the fields Fn−2 and Fn−1constitute a last frame image frm_last. Similar to the calculation ofthe inter-field matching information, a block with the pixel point to beinterpolated as a center is selected, and matching is performed after anMV, that is, (MV_(x), Mv_(y)), is calculated. For example, a 6×6 blockwhich takes the position of the current pixel point to be interpolatedas a center is selected, and is subjected to matching to obtain aninter-frame matching value sad_frame. The 6×6 block is merely anexample, and a block in another size may be selected as required formatching. In an embodiment, the inter-frame matching information may becalculated for the current frame and the next frame.

(c) The calculation of an edge direction of an image:

An edge direction of the current pixel point to be interpolated isdetected, and the detection of the edge direction is separatelyperformed in the current field Fn and the last field Fn−1, and may beimplemented with any general edge direction detection method, such as amethod using the Sobel operator. The two edge directions detected in thetwo fields (the current field and the last field) are denoted byangle_curr and angle1_last. The edge direction is divided into eightdirections from a fixed point from 0 to 180 degrees, and the eightdirections are represented by Direction 0 to Direction 7 respectively,as shown in FIG. 10. Direction 0 to Direction 7 are merely examples ofrepresenting the directions, and other values may be used to representthe directions, for example, the directions are represented directly byangles, or the directions are represented by two values indicating ahorizontal direction and a non-horizontal direction. In an embodiment,the edge direction may include the edge directions of the pixel pointsto be interpolated in the current field and the next field, or the edgedirection(s) of the pixel points to be interpolated in any one or moreof the last field, the current field and the next field.

(d) The determination of a drawing-feathering flag of an image

A “drawing-feathering” effect is caused by the fact that the motion ofan object changes significantly between two fields in an interlacedvideo. Drawing-feathering is generally characterized by a largedifference between adjacent rows of pixels (i.e., pixels of differentfields) in a synthesized frame formed by two adjacent fields. Thus, adrawing-feathering flag of an image is calculated by the algorithm usingthis characteristic. The calculation method is as follows:

the drawing-feathering intensity in the current frame image iscalculated in a synthesized frame formed by the current field and thelast field. In an embodiment, the drawing-feathering intensity in thecurrent frame image may be calculated in a synthesized frame formed bythe current field and the next field. Taking the calculation in thesynthesized frame formed by the current field and the last field as anexample, the calculation method is as follows:

an M×N region with the position of the current pixel point to beinterpolated as a center is selected from the current frame (thesynthesized frame formed by the current field and the last field) fordetection. In the following description of the calculation of thedrawing-feathering flag in the algorithm, 5×5 is taken as an example ofM×N, but the present disclosure is not limited thereto, and a block inanother size may be selected as required for the calculation. As shownin FIG. 11, a pixel point 1101 indicates the position of the currentpixel to be interpolated.

In the embodiment, two flags, bob_flag1 and bob_flag2, are calculatedwith the following method:

(d.1) the calculation of bob_flag1

An accumulated value of differences between pixel values of pixel pointsof heterogeneous field and an accumulated value of differences betweenpixel values of pixel points of homogeneous field in a column arecalculated column by column with the following method:

dif_parity_value[i]=|up_data[i]−curr_data[i]|+|curr_data[i]−down_data[i]|+|down_data[i]−down_down_data[i]|+|up_up_data[i]−up_data[i]|

same_parity_value[i]=|up_up_data[i]−curr_data[i]|+|up_data[i]−down_data[i]|++|curr_data[i]−down_down_data[i]|

where i=0 . . . N−1, for example, N is 5, up_up_data[i] is a luminancevalue of a pixel point in Row 0 and Column i in FIG. 11, up_data[i] is aluminance value of a pixel point in Row 1 and Column i in FIG. 11,curr_data[i] is a luminance value of a pixel point in Row 2 and Column iin FIG. 11, down_data[i] is a luminance value of a pixel point in Row 3and Column i in FIG. 11, and down_down_data[i] is a luminance value of apixel point in Row 4 and Column i in FIG. 11. The calculation ofbob_flag1 is described herein by taking N=5 as an example, and a similarcalculation method is applied for other values of N.

The number wave_cnt1 of the columns which satisfy the followingcondition is calculated for the N columns of data in the block,

same_parity_value[i]*coeff)<dif_parity_value[i]

where i=0˜4, and coeff is greater than 0. In an embodiment, coeff rangesfrom 0 to 20.

Whether the entire 5×5 region belongs to a drawing situation of Type 1is determined according to whether wave_cnt1 is greater than a thresholdNum1, and bob_flag1 is marked by a preset value (such as 1). Num1 rangesfrom 1 to N. In an embodiment, for example, Num1 is 3.

(d.2) The calculation of bob_flag2

In the calculation of bob_flag2, pixel values of all pixel points ineach horizontal row in the M×N block are accumulated to obtain Maccumulated values in total. The calculation of bob_flag2 is describedherein by taking M=5 and N=5 as an example.

$\begin{matrix}{{{{sum\_ value}{{\_ ver}\lbrack 0\rbrack}} = {\sum\limits_{i = 0}^{N - 1}{{up\_ up}{{\_ data}\lbrack i\rbrack}}}}{{{sum\_ value}{{\_ ver}\lbrack 1\rbrack}} = {\sum\limits_{i = 0}^{N - 1}{{up\_ data}\lbrack i\rbrack}}}{{{sum\_ value}{{\_ ver}\lbrack 2\rbrack}} = {\sum\limits_{i = 0}^{N - 1}{{curr\_ data}\lbrack i\rbrack}}}{{{sum\_ value}{{\_ ver}\lbrack 3\rbrack}} = {\sum\limits_{i = 0}^{N - 1}{{down\_ data}\lbrack i\rbrack}}}{{{sum\_ value}{{\_ ver}\lbrack 4\rbrack}} = {\sum\limits_{i = 0}^{N - 1}{{down\_ down}{{\_ data}\lbrack i\rbrack}}}}} & \;\end{matrix}$

Three thresholds for determining drawing situations are calculatedaccording to the above five values with the following method:

thr[j]=|(sum_value_ver[+1]*2−sum_value_ver[j]−sum_value_ver[j+2]|

where j=0˜M−3. When M=5, j=0˜2.

Differences of pixel values of pixel points of homogeneous field anddifferences of pixel values of pixel points of heterogeneous field arecalculated point by point for each column, but are not added up.

frame_diff[0][i]=|up_up_data[i]−curr_data[i]|

frame_diff[1][i]=|up_data[i]−down_data[i]|

frame_diff[2][i]=|curr_data[i]−down_down_data[i]|

field_diff[0][i]=|up_data[i]−curr_data[i]|

field_diff[1][i]=|curr_data[i]−down_data[i]|

field_diff[2][i]=|down_data[i]−down_down_data[i]|

where i=0˜N−1.

Whether the current column satisfies a drawing situation of Type 2 isdetermined according to the thresholds and the differences of the pixelvalues of the pixel points in each column. For all the columns in theM×N block, the number of the columns which satisfy all of the followingsix conditions is calculated. The six conditions are as follows:

thr[j]>frame_diff[j][i]*factor1

thr[j]<field_diff[j][i]*factor2

where j=0˜2 and i=0˜N−1. When each column is subjected to comparison todetermine whether the column satisfies the six conditions, the value ofi is kept unchanged and the value of j is taken from 0 to 2, so thecolumn will be subjected to comparison for six times. It is indicatedthat the column satisfies the drawing situation only if the columnsatisfies all the six conditions.

factor1 and factor2 are regulatory factors for drawing detection and aregreater than 0. In an embodiment, factor1 and factor2 range from 0 to20.

In the M×N block, the number wave_cnt2 of the columns which satisfy allthe above six conditions are calculated. If wave_cnt2 is greater thanNum2, bob_flag2 in the 5×5 region is marked by 1. Num2 ranges from 1 toN. In an embodiment, for example, Num2 is 3.

(d.3) In the current 5×5 region, the drawing-feathering flag bob_flag atthe pixel point to be interpolated is set to 1 when bob_flag1 orbob_flag2 is marked by 1. In an embodiment, setting bob_flag to 1 ismerely an example, and bob_flag can be set to other values as requiredto indicate that the current drawing-feathering intensity satisfies thedrawing intensity condition. In other embodiments, bob_flag2 is notcalculated when bob_flag1=1 is determined, and the drawing-featheringflag bob_flag at the pixel point to be interpolated is set to 1; orbob_flag1 is not calculated when bob_flag2=1 is determined, and thedrawing-feathering flag bob_flag at the pixel point to be interpolatedis set to 1; or bob_flag is not set, and bob_flag1 and bob_flag2 aredirectly output.

The above steps (a) to (d) can be performed in parallel in the processof calculating the image content characteristics.

At the step 404, a corresponding result is selected from a result of MAde-interlacing and a result of MC de-interlacing according to the imagecontent characteristics and the selected result is output.

In other embodiments, it is possible to first determine whether thede-interlacing processing based on MA or the de-interlacing processingbased or MC is to be performed. If the de-interlacing processing basedon MA is to be performed, the de-interlacing processing based or MC isnot required.

In an embodiment, the result of de-interlacing based on MA is selectedif one of the follow conditions is satisfied, and the result ofde-interlacing based on MC is selected if none of the follow conditionsis satisfied.

MV Conditions:

(1) A current MV is 0, indicating that the image is static; and

(2) An absolute value of any component of the current MV is greater thanT integer pixels, and T is greater than 0, which indicates large motionintensity. In an embodiment, for example, T is 9. The de-interlacingalgorithm based on MA is adopted in the case of large motion intensity;

SAD Conditions:

(3) sad_field>sad_field_thr1 and sad_frame>sad_fram_thr1. The smallersad_field is, the higher the inter-field similarity is; and the smallersad_frame is, the higher the inter-frame similarity is;

(4) sad_field>sad_field_thr2 and sad_frame>sad_frame_thr2;

(5) sad_field>sad_frame and sad_frame>sad_frame_thr3;

where sad_field_thr1 ranges from 0 to 300;

sad_field_thr2 ranges from 200 to 600;

sad_frame_thr1 ranges from 200 to 700;

sad_frame_thr2 ranges from 100 to 500;

sad_frame_thr3 ranges from 0 to 300;

Edge Angle Condition:

(6) angle_curr>0 or angle1_last>0. According to the above description,0˜7 are used to indicate directions from 0 to 180 degrees, soangle_curr>0 or angle1_last>0 indicates that a current edge direction isa non-horizontal direction. If other values are used to indicate thedirections, the expression may be changed accordingly. When the edgedirection is a non-horizontal direction, the de-interlacing algorithmbased on MA is adopted.

Drawing Condition:

(7) bob_flag=1, indicating large differences between rows. Thede-interlacing algorithm based on MA is adopted in the case of largedifferences between rows.

In an embodiment, the conditions may be any one or more of the aboveconditions (1) to (7).

In at least one embodiment of the present disclosure, according to thefeatures of the de-interlacing algorithm based on MA and thede-interlacing algorithm based on MC and the image content of the video,a suitable result is adaptively selected from the results of the abovetwo algorithms and is output. As the de-interlacing processing based onMA uses intra-field directional interpolation for motions, theinformation of some horizontal edge textures may be lost, resulting inimage flickering and blurring. In the case where an intra-fielddirection is determined inaccurately, image noises may be caused. Thede-interlacing processing based on MC is very sensitive to the MVobtained by the ME, and thus has a high requirement for accuracy of theMV obtained by the ME. The MV may be not reliable enough when an objectrotates or is deformed, which may cause compensation errors. As shown byactual display of a television and experiments, the solution provided byat least one embodiment of the present disclosure overcomes the defectsof the MA-based algorithm, that is, image flickering and blurring, andalso overcomes the defects of the MC-based algorithm, that is, highrequirement for MV accuracy, high sensitivity to MVs and strongpossibility of generating the noises, thereby enhancing the overallimage effect. In addition, as the present disclosure proposes thecombination of two algorithms, some de-interlacing devices in theexisting arts can be improved well accordingly.

As shown in FIG. 12, an embodiment of the present disclosure provides ade-interlacing processing device 120, including a memory 1210 storing aprogram, and a processor 1220. When the program is read and executed bythe processor 1220, the method according to any one embodiment isimplemented.

As shown in FIG. 13, at least one embodiment of the present disclosureprovides a computer-readable storage medium 130 storing one or moreprograms 131 which are executable by one or more processors to performthe method according to any one embodiment.

The functional modules/units in all or some of the steps, the systems,and the devices in the method disclosed above may be implemented assoftware, firmware, hardware, or suitable combinations thereof. Ifimplemented as hardware, the division between the functionalmodules/units stated above is not necessarily corresponding to thedivision of physical components; for example, one physical component mayhave a plurality of functions, or one function or step may be performedthrough cooperation of one or more physical components. Some or all ofthe components may be implemented as software executed by a processor,such as a digital signal processor or a microprocessor, or may beimplemented as hardware, or may be implemented as an integrated circuit,such as an application specific integrated circuit. Such software may bedistributed on computer-readable media, which may include computerstorage media (or non-transitory media) and communication media (ortransitory media). The term “computer storage media” includesvolatile/nonvolatile and removable/non-removable media used in anymethod or technology for storing information (such as computer-readableinstructions, data structures, program modules and other data). Thecomputer storage media include a Random Access Memory (RAM), a Read-OnlyMemory (ROM), an Electrically Erasable Programmable Read-Only Memory(EEPROM), a Flash Memory or other memory techniques, a Compact Disc ReadOnly Memory (CD-ROM), a Digital Video Disk (DVD) or other optical discs,a magnetic cassette, a magnetic tape, a magnetic disk or other magneticstorage devices, or any other media which can be configured to store thedesired information and can be accessed by a computer. In addition, thecommunication media generally include computer-readable instructions,data structures, program modules, or other data in modulated datasignals such as carrier wave or other transmission mechanism, and mayinclude any information delivery medium.

1. A de-interlacing processing method, comprising: acquiring imagecontent characteristic information of a pixel point to be interpolated;and determining according to the image content characteristicinformation whether a de-interlacing algorithm based on motion adaptiveor a de-interlacing algorithm based on motion compensation is adopted toperform de-interlacing processing.
 2. The method according to claim 1,wherein the image content characteristic information comprises at leastone of motion vector information, inter-field matching information,inter-frame matching information, edge direction information, ordrawing-feathering intensity information.
 3. The method according toclaim 2, wherein the step of determining according to the image contentcharacteristic information whether the de-interlacing algorithm based onmotion adaptive or the de-interlacing algorithm based on motioncompensation is adopted to perform de-interlacing processing comprises:when one of the following conditions is satisfied, adopting thede-interlacing algorithm based on motion adaptive to performde-interlacing processing; and when none of the following conditions issatisfied, adopting the de-interlacing algorithm based on motioncompensation to perform de-interlacing processing; wherein, theconditions comprise at least one of: a motion vector of the pixel pointto be interpolated is 0; an absolute value of any component of themotion vector of the pixel point to be interpolated is greater than apreset number of integer pixels; the inter-field matching information ofthe pixel point to be interpolated is greater than a first inter-fieldmatching threshold, and the inter-frame matching information of thepixel point to be interpolated is greater than a first inter-framematching threshold; the inter-field matching information of the pixelpoint to be interpolated is greater than a second inter-field matchingthreshold, and the inter-frame matching information of the pixel pointto be interpolated is greater than a second inter-frame matchingthreshold; the inter-field matching information of the pixel point to beinterpolated is greater than the inter-frame matching information, andthe inter-frame matching information of the pixel point to beinterpolated is greater than a third inter-frame matching threshold;first edge direction information of the pixel point to be interpolatedin a current field indicates a non-horizontal direction; second edgedirection information of the pixel point to be interpolated in a lastfield relative to the current field indicates a non-horizontaldirection; third edge direction information of the pixel point to beinterpolated in a next field relative to the current field indicates anon-horizontal direction; or the drawing-feathering intensityinformation of the pixel point to be interpolated is greater than adrawing intensity threshold.
 4. The method according to claim 3, whereinthe first inter-field matching threshold ranges from 0 to 300; thesecond inter-field matching threshold ranges from 200 to 600; the firstinter-frame matching threshold ranges from 200 to 700; the secondinter-frame matching threshold ranges from 100 to 500; and the thirdinter-frame matching threshold ranges from 0 to
 300. 5. The methodaccording to claim 2, wherein the inter-field matching information isdetermined with the following method: selecting a first pixel blockcomposed of M pixels in a last row relative to a current row where thepixel point to be interpolated is located and a second pixel blockcomposed of M pixels in a next row relative to the current row from acurrent field, determining matched blocks of the first pixel block andthe second pixel block in a last field relative to the current field,obtaining a first sum of absolute differences according to the firstpixel block and the matched block thereof, and a second sum of absolutedifferences according to the second pixel block and the matched blockthereof, and taking a maximum value of the first sum of absolutedifferences and the second sum of absolute differences as theinter-field matching information, wherein a central position of the Mpixels in the last row and a central position of the M pixels in thenext row are in a same column as the pixel point to be interpolated, andM is a positive integer.
 6. The method according to claim 2, wherein theinter-frame matching information is determined with the followingmethod: forming a current frame from a current field where the pixelpoint to be interpolated is located and a next field relative to thecurrent field, selecting a pixel block in a preset size with the pixelpoint to be interpolated taken as a center, and matching the pixel blockwith a pixel block in a last frame relative to the current frame toobtain the inter-frame matching information.
 7. The method according toclaim 3, wherein the drawing-feathering intensity information isdetermined with at least one of the following methods: an M×N pixelblock with the pixel point to be interpolated as a center is taken froma synthesized frame composed of a current field and a last fieldrelative to the current field; for the M×N pixel block, an accumulatedvalue of differences between pixel values corresponding to adjacentpixel points of heterogeneous field in a column and an accumulated valueof differences between pixel values corresponding to adjacent pixelpoints of homogeneous field in the column are calculated column bycolumn; and a total number of the columns satisfyingsame_parity_value[i]*coeff<dif_parity_value[i] is obtained, whereinsame_parity_value[i] is an accumulated value of differences betweenpixel values corresponding to adjacent pixel points of homogeneous fieldin Column i in the M×N pixel block, dif_parity_value[i] is anaccumulated value of differences between pixel values corresponding toadjacent pixel points of heterogeneous field in Column i in the M×Npixel block, i=0˜N−1, and coeff is greater than 0; and, when the totalnumber of the columns satisfyingsame_parity_value[i]*coeff<dif_parity_value[i] is greater than a firstthreshold, the drawing-feathering intensity information is greater thanthe drawing intensity threshold; for the M×N pixel block, an accumulatedvalue of pixels in each row is acquired to obtain M accumulated valuessum_value_ver[l], where l=0˜M−1; (M−2) thresholdsthr[j]=|(sum_value_ver[j+1]*2−sum_value_ver[j]−sum_value_ver[j+2]| areobtained according to the M accumulated values, where j=0˜M−3, M isgreater than or equal to 3, and N is greater than or equal to 1;differences between pixel values corresponding to adjacent pixel pointsof homogeneous field and differences between pixel values correspondingto adjacent pixel points of heterogeneous field are calculated point bypoint:frame_diff[j][i]=|Y[j][i]−Y[j+2][i]|field_diff[j][i]=|Y[j][i]−Y[j+1][i]| where i=0˜N−1; when a total numberof columns satisfying $\begin{matrix}{{{{thr}\lbrack j\rbrack} > {{{{frame\_ diff}\lbrack j\rbrack}\lbrack i\rbrack}^{*}{factor}\; 1}}{{{thr}\lbrack j\rbrack} < {{{{field\_ diff}\lbrack j\rbrack}\lbrack i\rbrack}^{*}{factor}\; 2}}} & \;\end{matrix}$ is greater than a second threshold, the drawing-featheringintensity information is greater than the drawing intensity threshold,where factor1 and factor2 are regulatory factors for drawing detectionand are greater than 0, Y[j][i] is a value of a pixel point in Row j andColumn i in the M×N pixel block, frame_diff[j][i] is a differencebetween pixel values corresponding to adjacent pixel points ofhomogeneous field for the pixel point in Row j and Column i in the M×Npixel block, and field_diff[j][i] is a difference between pixel valuescorresponding to adjacent pixel points of heterogeneous field for thepixel point in Row j and Column i in the M×N pixel block.
 8. The methodaccording to claim 1, wherein the step of performing de-interlacingprocessing using the de-interlacing algorithm based on motioncompensation comprising: acquiring a first value of the pixel point tobe interpolated calculated by the de-interlacing algorithm based onmotion adaptive; acquiring a second value of the pixel point to beinterpolated calculated by a de-interlacing algorithm based on forwardmotion compensation; acquiring a third value of the pixel point to beinterpolated calculated by a de-interlacing algorithm based on backwardmotion compensation; and performing median filtering on the first value,the second value and the third value, and taking a result of the medianfiltering as a value of the pixel point to be interpolated calculated bythe de-interlacing algorithm based on motion compensation.
 9. Ade-interlacing processing device, comprising a memory storing a program,and a processor, wherein the method according to claim 1 is implementedwhen the program is read and executed by the processor.
 10. Acomputer-readable storage medium storing one or more programs, whereinthe one or more programs are executable by one or more processors toperform the method according to claim
 1. 11. The method according toclaim 2, wherein the step of performing de-interlacing processing usingthe de-interlacing algorithm based on motion compensation comprising:acquiring a first value of the pixel point to be interpolated calculatedby the de-interlacing algorithm based on motion adaptive; acquiring asecond value of the pixel point to be interpolated calculated by ade-interlacing algorithm based on forward motion compensation; acquiringa third value of the pixel point to be interpolated calculated by ade-interlacing algorithm based on backward motion compensation; andperforming median filtering on the first value, the second value and thethird value, and taking a result of the median filtering as a value ofthe pixel point to be interpolated calculated by the de-interlacingalgorithm based on motion compensation.
 12. The method according toclaim 3, wherein the step of performing de-interlacing processing usingthe de-interlacing algorithm based on motion compensation comprising:acquiring a first value of the pixel point to be interpolated calculatedby the de-interlacing algorithm based on motion adaptive; acquiring asecond value of the pixel point to be interpolated calculated by ade-interlacing algorithm based on forward motion compensation; acquiringa third value of the pixel point to be interpolated calculated by ade-interlacing algorithm based on backward motion compensation; andperforming median filtering on the first value, the second value and thethird value, and taking a result of the median filtering as a value ofthe pixel point to be interpolated calculated by the de-interlacingalgorithm based on motion compensation.
 13. The method according toclaim 4, wherein the step of performing de-interlacing processing usingthe de-interlacing algorithm based on motion compensation comprising:acquiring a first value of the pixel point to be interpolated calculatedby the de-interlacing algorithm based on motion adaptive; acquiring asecond value of the pixel point to be interpolated calculated by ade-interlacing algorithm based on forward motion compensation; acquiringa third value of the pixel point to be interpolated calculated by ade-interlacing algorithm based on backward motion compensation; andperforming median filtering on the first value, the second value and thethird value, and taking a result of the median filtering as a value ofthe pixel point to be interpolated calculated by the de-interlacingalgorithm based on motion compensation.
 14. The method according toclaim 5, wherein the step of performing de-interlacing processing usingthe de-interlacing algorithm based on motion compensation comprising:acquiring a first value of the pixel point to be interpolated calculatedby the de-interlacing algorithm based on motion adaptive; acquiring asecond value of the pixel point to be interpolated calculated by ade-interlacing algorithm based on forward motion compensation; acquiringa third value of the pixel point to be interpolated calculated by ade-interlacing algorithm based on backward motion compensation; andperforming median filtering on the first value, the second value and thethird value, and taking a result of the median filtering as a value ofthe pixel point to be interpolated calculated by the de-interlacingalgorithm based on motion compensation.
 15. The method according toclaim 6, wherein the step of performing de-interlacing processing usingthe de-interlacing algorithm based on motion compensation comprising:acquiring a first value of the pixel point to be interpolated calculatedby the de-interlacing algorithm based on motion adaptive; acquiring asecond value of the pixel point to be interpolated calculated by ade-interlacing algorithm based on forward motion compensation; acquiringa third value of the pixel point to be interpolated calculated by ade-interlacing algorithm based on backward motion compensation; andperforming median filtering on the first value, the second value and thethird value, and taking a result of the median filtering as a value ofthe pixel point to be interpolated calculated by the de-interlacingalgorithm based on motion compensation.
 16. The method according toclaim 7, wherein the step of performing de-interlacing processing usingthe de-interlacing algorithm based on motion compensation comprising:acquiring a first value of the pixel point to be interpolated calculatedby the de-interlacing algorithm based on motion adaptive; acquiring asecond value of the pixel point to be interpolated calculated by ade-interlacing algorithm based on forward motion compensation; acquiringa third value of the pixel point to be interpolated calculated by ade-interlacing algorithm based on backward motion compensation; andperforming median filtering on the first value, the second value and thethird value, and taking a result of the median filtering as a value ofthe pixel point to be interpolated calculated by the de-interlacingalgorithm based on motion compensation.
 17. A de-interlacing processingdevice, comprising a memory storing a program, and a processor, whereinthe method according to claim 2 is implemented when the program is readand executed by the processor.
 18. A de-interlacing processing device,comprising a memory storing a program, and a processor, wherein themethod according to claim 3 is implemented when the program is read andexecuted by the processor.
 19. A de-interlacing processing device,comprising a memory storing a program, and a processor, wherein themethod according to claim 4 is implemented when the program is read andexecuted by the processor.
 20. A de-interlacing processing device,comprising a memory storing a program, and a processor, wherein themethod according to claim 5 is implemented when the program is read andexecuted by the processor.